Data Science with Python Training

Description

What is Data Science?

Data science is a field of providing meaningful information based on large amounts of complex data. Data science, or data-driven science, combines different fields of work in statistics and computation in order to interpret data for the purpose of decision making.

Why Data Science?

The new-found love for data science in today’s computing world isn’t unjustified. Ranked as the hottest job on offer in the coming years by Harvard Business Review.

The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020.

Who is a Data Scientist?

Data Scientists are “Part analyst, Part artist”.

The literal meaning for a data scientist is who practised and acquired a good amount of knowledge in data science course. 😊

Someone who gained knowledge and skills in analytics, computer science, mathematics, statistics, data visualisations and communication as well as business and strategy.

Why so much demand for Data Science?

The below viz explains all about how much demand and shortage of skills is increasing year on year.

The following topics will be covered as part of Data Science with Python Training.

Statistics

Introduction to Statistics

Different Areas of Statistics

Central Tendency

Correlation, Covariance, Collinearity

Hypothesis Testing

ANOVA

Chi-square Test.

Python Essentials – Core

Overview of Python – Starting with Python

Python Packages : Numpy, scify, pandas, scikitlearn, nltk etc

Basic Python Programming – Hands-on/Demo

Advanced Python Programming – Hands-on/Demo

Assignment – 1

Introduction To Data Science

Intoduction to Data Analytics

Applications

DS Use-Cases

Exploratory Data Analysis

Missing Value Analysis

Outlier Analysis

Hands-on Demo – Python

​Data Pre-Processing

Variable Importance

Normalization

Sampling

Hands-on Demo – Python

​Assignment – 2

Introduction to Machine Learning – Supervised ML

Introduction to Machine Learning

Decision Trees

Random Forests

Linear Regression

Logistic Regression

Hands-on Demo – Python

​Advanced Machine Learning – (Supervised + Unsupervided) ML

Visualization

KNN

Naive Bayes

Cluster Analysis

Hands-on Demo – Python

​Assignment – 3

Natural Language Processing

Introduction to Text Mining

Text Preprocessing

TF-IDF

Word Cloud

Sentiment Analysis

Hands-on Demo – Python

Time Series

Introduction to Time Series

Time Series Variables

ARIMA Model for Forecasting

Exponential Smoothing Models

Hands-on Demo – Python

​Assignment – 4

Case Study

Regression Case Study

Classification Case Study

Time Series Case Study

​Assignment – 5

Introduction to Deep Learning

Final Project

Pre-requisites :

Basic statistics knowledge and any computer programming language is preferred.